Ionic liquids (ILs) are promising nonderivatizing solvents for the dissolution of cellulose and lignin in biomass pretreatment processes, which are, however, retarded by sluggish dynamics. Recent investigations showed that cosolvents such as dimethyl sulfoxide (DMSO) can accelerate the dissolution dramatically. On the other hand, water is used as a common antisolvent to regenerate cellulose from solutions. To understand the co-/antisolvent effects in dissolving cellulose by ILs, we performed molecular dynamics simulations of the interfaces between an Iβ cellulose crystal and different solvent systems, including ILs, DMSO, water, and mixed solvent systems. The density profiles and pair energy distributions (PEDs) show that the anions interact much more strongly with the cellulose surface than the cations, which is responsible for the dissolution of cellulose. It was found that the number of chloride ions in contact with cellulose does not cause the co-/antisolvent effect. In contrast, the cellulose–chloride PEDs are sensitive to the addition of molecular solvents, such as DMSO and water. Detailed analyses show that multiple hydrogen-bond (HB) patterns are formed between chloride and the hydroxyl groups of cellulose that are noticeably changed in the presence of DMSO or water. A combined analyses of both the PEDs and HB patterns can provide valuable information about the enhancement of cellulose dissolution. The simulation results in this work present useful knowledge for the design of solvent systems for dissolving cellulose or other types of biomass.

We use the multiscale simulation approach, which combines the first-principles calculations and grand canonical Monte Carlo simulations, to comprehensively study the doping of a series of alkali (Li, Na, and K), alkaline-earth (Be, Mg, and Ca), and transition (Sc and Ti) metals in nanoporous covalent organic frameworks (COFs), and the effects of the doped metals on CO2 capture. The results indicate that, among all the metals studied, Li, Sc, and Ti can bind with COFs stably, while Be, Mg, and Ca cannot, because the binding of Be, Mg, and Ca with COFs is very weak. Furthermore, Li, Sc, and Ti can improve the uptakes of CO2 in COFs significantly. However, the binding energy of a CO2 molecule with Sc and Ti exceeds the lower limit of chemisorptions and, thus, suffers from the difficulty of desorption. By the comparative studies above, it is found that Li is the best surface modifier of COFs for CO2 capture among all the metals studied. Therefore, we further investigate the uptakes of CO2 in the Li-doped COFs. Our simulation results show that at 298 K and 1 bar, the excess CO2 uptakes of the Li-doped COF-102 and COF-105 reach 409 and 344 mg/g, which are about eight and four times those in the nondoped ones, respectively. As the pressure increases to 40 bar, the CO2 uptakes of the Li-doped COF-102 and COF-105 reach 1349 and 2266 mg/g at 298 K, respectively, which are among the reported highest scores to date. In summary, doping of metals in porous COFs provides an efficient approach for enhancing CO2 capture.Keywords: CO2 capture; covalent organic frameworks; first-principles calculations; grand canonical Monte Carlo simulation; metal-doping

A multiscale theoretical method, which combines the first-principles calculation and grand canonical Monte Carlo (GCMC) simulation, is used to investigate the adsorption capacities of hydrogen in nondoped and Li-doped covalent organic borosilicate frameworks (COF-202). Our simulations indicate that the total gravimetric and volumetric hydrogen uptakes of COF-202 reach 7.83 wt % and 44.37 g/L at T = 77 K and p = 100 bar, respectively. To enhance the hydrogen storage capacity of COF-202, the doping of Li atoms in COF-202 is studied systematically. First, the first-principles calculations are performed to investigate the possible adsorption sites and the quantity of Li atoms doped in COF-202. Our results prove that, for a single Li atom, the top of the phenyl groups in COF-202 is the most favorable adsorption site; for coadsorption of two Li atoms, with one adsorbed at the top site of a phenyl group and the other at its neighboring interstitial site between the phenyl group and the B−O−Si linkage is the most favorable adsorption mode. Our GCMC simulations predict that the total gravimetric and volumetric uptakes of hydrogen in the Li-doped COF-202 reach 4.39 wt % and 25.86 g/L at T = 298 K and p = 100 bar, respectively, where the weight percent of Li equals to 7.90 wt %. This suggests that the Li-doped COF-202 is one of the most promising candidates for hydrogen storage at room temperature.

Polymer nanocomposites (PNCs) often exhibit excellent mechanical, thermal, electrical and optical properties, because they combine the performances of both polymers and inorganic or organic nanoparticles. Recently, computer modeling and simulation are playing an important role in exploring the reinforcement mechanism of the PNCs and even the design of functional PNCs. This report provides an overview of the progress made in past decades in the investigation of the static, rheological and mechanical properties of polymer nanocomposites studied by computer modeling and simulation. Emphases are placed on exploring the mechanisms at the molecular level for the dispersion of nanoparticles in nanocomposites, the effects of nanoparticles on chain conformation and glass transition temperature (Tg), as well as viscoelastic and mechanical properties. Finally, some future challenges and opportunities in computer modeling and simulation of PNCs are addressed.

A theoretical method, which combines the first-principle calculations and a canonical Monte Carlo (CMC) simulation, was used to study the structures of Au clusters with sizes of 25–54 atoms supported on the MgO(1 0 0) surface. Based on a potential energy surface (PES) fitted to the first-principle calculations, an effective approach was derived to model the Au–MgO(1 0 0) interaction. The second moment approximation to the tight-binding potential (TB-SMA) was used to model the Au–Au interactions in the CMC simulation. It is found that the Au clusters with sizes of 25–54 atoms supported on the MgO(1 0 0) surface possess an ordered layered fcc epitaxial structure.

In this work, a coarse-grained model for a kind of membrane protein, the mechanosensitive channel of small conductance (MscS), is proposed. The basic structure of the MscS is preserved when the protein is coarse-grained. For the coarse-grained model, the channels show two different states, namely the open and closed states, depending on the model parameters. Under the same membrane tension, the state of the ion channel is found to be critically determined by the protein structure, especially the length of the transmembrane α-helix. It is also found that for the protein with certain size, the gating transition occurs when the membrane tension is applied, resembling in a real mechanosensitive channel.

A general synthesis strategy to prepare metal nanostructures by self-assembly was proposed by molecular dynamics (MD) simulation. In this simulating synthesis strategy, the metal nanostructures were generated by the self-assembly of the amorphous nanoparticles with the attractive forces of the nanoparticle−nanoparticle interactions by the annealing MD method at high temperatures, and finally, the resulting amorphous metal nanostructures were cooled to 10 K, which could resemble the nanoparticle self-assembly in experiment. By using the simulating synthesis, we obtained the full atomistic models of the shape-controlled metal nanostructures, including Au, Ag−Au, and beaded Ag−Cu nanorods, triangular and hexagonal Ag nanoplates, triangular Ag−Au and hexagonal Au, cubic hollow Fe, and Ag−Au nanoframes. It is found that these models are in good agreement with the experimental results. Moreover, we predicted a new metal nanostructure, Au nanoporous framework architecture, which has not been reported in experiment, by self-assembly of the Au nanoparticles. The predicted architecture possesses three-dimensional periodic inner-connecting channels and cavities. It is believed that our simulating synthesis approach will help facilitate the preparation and design of novel metal nanostructures in experiment.

Understanding the composition effect on the melting processes of bimetallic clusters is important for their applications. Here, we report the relationship between the melting point and the metal composition for the 55-atom icosahedral Ag–Pd bimetallic clusters by canonical Monte Carlo simulations, using the second-moment approximation of the tight-binding potentials (TB-SMA) for the metal–metal interactions. Abnormal melting phenomena for the systems of interest are found. Our simulation results reveal that the dependence of the melting point on the composition is not a monotonic change, but experiences three different stages. The melting temperatures of the Ag–Pd bimetallic clusters increase monotonically with the concentration of the Ag atoms first. Then, they reach a plateau presenting almost a constant value. Finally, they decrease sharply at a specific composition. The main reason for this change can be explained in terms of the relative stability of the Ag–Pd bimetallic clusters at different compositions. The results suggest that the more stable the cluster, the higher the melting point for the 55-atom icosahedral Ag–Pd bimetallic clusters at different compositions.

Permeation and separation of H2/CO binary mixtures in nanoporous carbon membranes are investigated by non-equilibrium molecular dynamics simulations. The carbon membrane pores are modeled as slit-like pores with entrance and exit. The buffer regions between the control volumes and membrane pores are employed to take into account the effects of the entrance and exit of the membrane pores. The effects of pore width, separation temperature, feed gas pressure, the molar fraction of hydrogen, and membrane thickness on flux and dynamic separation factor are discussed. The simulation results indicate that the pore width strongly affects the flux and dynamic separation factor. In addition, molecular sieving dominates the separation of H2/CO mixtures, when the pore width is smaller by about 0.64 nm, and, in this case, the dynamic separation factor reaches 52.88 at 0.5 MPa and 300 K. The dynamic separation factor increases with the separation temperature and the decrease of feed gas pressure, while changes slightly with the molar fraction of H2 in the feed gas. Moreover, the dynamic separation factor increases with membrane thickness at the pore width of 0.64 nm, while decreases at the pore width of 1.01 nm due to different separation mechanisms.

A hybrid cylindrical model for characterization of MCM-41 by density functional theory (DFT) is proposed in this work, where the surface heterogeneity of MCM-41 is taken into account by using a hybrid potential model to represent the interactions between a pore wall and molecules inside the pore. This model consists of two parts: (1) the potential energies from the oxygen atoms inside the wall, represented by the potential model proposed by our group; (2) the potential energies from the silanol coverage and/or other unknown factors in the surface of the channel of MCM-41, represented by the cylindrical surface potential function of Tjatjopoulos et al. (G. J. Tjatjopoulos, D. L. Feke and J. A. Mann, J. Phys. Chem., 1988, 92, 4006–4007). To test the new model, the DFT method was used to calculate the adsorption isotherm of nitrogen in MCM-41 at 77 K. The isotherm calculated is compared with the experimental data as well as the calculated results of Maddox et al., who divided the surface of MCM-41 into eight sectors and adopted different parameters for each sector to consider the heterogeneity of the surface. Compared with the work of Maddox et al. (M. W. Maddox, J. P. Olivier and K. E. Gubbins, Langmuir, 1997, 13, 1737–1745), our model gives a much better fit to the experimental isotherm of nitrogen at 77 K in the pressure range of P/P0 = 0.2–0.5 with much less parameter and computation effort, where phase transition and capillary condensation occur. Furthermore, the relationship between the reduced pressure, at which capillary condensation takes place, and the pore diameter by the hybrid model is in good agreement with that obtained by Maddox et al. In addition, adsorption and phase behavior of methane and ethane are studied by the model, and the calculated results also coincide well with the experimental isotherms of methane and ethane at 264 K–373 K. Therefore, the hybrid potential model incorporating into the DFT method provides a useful tool for characterization of MCM-41.

Polymer nanocomposites (PNCs) often exhibit excellent mechanical, thermal, electrical and optical properties, because they combine the performances of both polymers and inorganic or organic nanoparticles. Recently, computer modeling and simulation are playing an important role in exploring the reinforcement mechanism of the PNCs and even the design of functional PNCs. This report provides an overview of the progress made in past decades in the investigation of the static, rheological and mechanical properties of polymer nanocomposites studied by computer modeling and simulation. Emphases are placed on exploring the mechanisms at the molecular level for the dispersion of nanoparticles in nanocomposites, the effects of nanoparticles on chain conformation and glass transition temperature (Tg), as well as viscoelastic and mechanical properties. Finally, some future challenges and opportunities in computer modeling and simulation of PNCs are addressed.

Understanding the composition effect on the melting processes of bimetallic clusters is important for their applications. Here, we report the relationship between the melting point and the metal composition for the 55-atom icosahedral Ag–Pd bimetallic clusters by canonical Monte Carlo simulations, using the second-moment approximation of the tight-binding potentials (TB-SMA) for the metal–metal interactions. Abnormal melting phenomena for the systems of interest are found. Our simulation results reveal that the dependence of the melting point on the composition is not a monotonic change, but experiences three different stages. The melting temperatures of the Ag–Pd bimetallic clusters increase monotonically with the concentration of the Ag atoms first. Then, they reach a plateau presenting almost a constant value. Finally, they decrease sharply at a specific composition. The main reason for this change can be explained in terms of the relative stability of the Ag–Pd bimetallic clusters at different compositions. The results suggest that the more stable the cluster, the higher the melting point for the 55-atom icosahedral Ag–Pd bimetallic clusters at different compositions.